基于前馈信号参考的可变收敛列车噪声主动控制算法

Variable convergence train noise active control algorithm based on feedforward reference

研究了一种基于前馈信号参考的可变收敛列车噪声主动控制算法,通过构建基于前馈信号参考的可变收敛函数,改善系统非零失调问题,并应用于列车低频噪声降噪中。仿真结果表明,该算法能够提高收敛速度、跟踪速率和稳态误差之间的均衡性。试验结果表明,该算法对于频率低于1 000 Hz的列车低频噪声在目标区域内平均降噪量约为12.0 d B,与固定收敛FxLMS算法、可变收敛NLMS算法和SVSLMS算法相比,具有最高约3.6 dB的降噪优势。

An active control algorithm for train noise based on feed-forward reference with variable convergence was studied.By constructing a variable convergence function based on the feed-forward signal reference,the non-zero offset problem of the system was improved.Then it was applied to the low-frequency noise reduction of trains.Simulation results show that the algorithm can improve the balance between convergence speed,tracking speed and steady-state error.And the experimental results show that the algorithm achieves an average noise reduction of 12.0 dB for low-frequency train noise which below 1000 Hz in the target area.Compared with the fixedconvergence FxLMS,variable-convergence NLMS,and SVSLMS control algorithms,it has the advantage of noise reduction up to about3.6 d B.